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In this study, a structure with high accuracy for the classification of Electromyographic (EMG) signals is used. This structure is a general-purpose artificial neural network which was proposed in previous studies. This network, called the Linear Weighted Radial Base Function Network (LWRBF) due to the use of a feature extraction strategy which includes Discrete Wavelet Transform (DWT), Principal...
There are a considerable number of feature extraction methods to be used for the classification of electromyographic (EMG) signals. These features are obtained from the raw EMG data by time domain and time-frequency domain transformations. Time-frequency domain originated features involve a high computational cost. Hence, for the EMG controlled electromechanical prostheses to be readily usable, time...
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